The present invention relates to the field of cellular network systems. In particular, the present invention provides for efficient modeling and analysis of cellular handoff decision mechanisms used in cellular networks.
In cellular networks, each mobile station (MS) maintains connectivity via an active set of base stations (BS). A handoff algorithm determines the dynamics of the active set as the MS moves through the network. In hard handoff, the MS is “handed off” from one BS to another BS as it leaves the cell coverage area of the first BS and enters that of the second BS. In this case, the active set of an MS consists of at most one BS at any given time. Hard handoff algorithms are used in the GSM (Global System for Mobile Communications) and GPRS wireless networking standards and are still under active investigation for use in High Data Rate (HDR) services.
Wireless technologies based on CDMA generally employ soft handoff, whereby the MS maintains an active set that may contain multiple BSs. A soft handoff occurs whenever a BS enters or leaves the active set of an MS. Soft handoff algorithms are used in the IS-95 and cdma2000 standards and have been proposed for use in the WCDMA standard.
The handoff behavior of mobile units in a cellular network may be critical to the overall performance of the network in terms of quality-of-service, resource utilization, and signaling load. Ideally, the network should maintain seamless quality-of-service for an active mobile user engaged in a call as it traverses cell boundaries. Even when the mobile station is in the idle state, the choice of cell assignment set may impact the network in terms of resource utilization and signaling load, as well as the quality-of-service experienced by the MS when it transits to the active state. Thus, the proper design and dimensioning of the handoff algorithm may be crucial to the deployment of a cellular network.
What is needed is a discrete-time framework for analyzing the performance of handoff algorithms executed by an MS based on pilot signal strength measurements from candidate BSs.
Vijayan and Holtzman were among the first to propose an analytical model for handoff based on signal strength measurements. (See R. Vijayan and J. M. Holtzman, “A Model for Analyzing Handoff Algorithms,” IEEE Trans. on Vehicular Technology, vol. 42, pp. 351–356, August 1993.) They modeled the trajectory of a mobile station as a continuous-time process wherein handoffs corresponded to the level-crossing events of the relative signal strength between two candidate base stations. They further argued that the level-crossing events could be modeled approximately by Poisson processes with time-varying rate functions. A limitation of the Poisson level-crossing model is that it is accurate only for relatively high level-crossings. Furthermore, when the model is applied to the realistic scenario of sampled signal measurements, the sampling interval must be sufficiently small for the model assumptions to hold. Another limitation of this model is that it is applicable only to relative signal strength measurements and may not accommodate constraints on absolute signal strength.
Subsequently, Zhang and Holtzman proposed an alternative approach to analyzing handoff based on the Gaussian properties of the sampled and processed received signal strengths. (See N. Zhang and J. M. Holtzman, “Analysis of Handoff Algorithms Using Both Absolute and Relative Measurements,” IEEE Trans. on Vehicular Technology, vol. 45, pp. 174–179, February 1996.) Their approach incorporated absolute signal strength thresholds in the handoff algorithm. Approximations for the handoff probabilities are obtained by making some simplifying assumptions. However, one skilled in the art will observe that the approximate formulas disclosed in this article may be inaccurate, particularly when relative signal strength alone is used as the basis for handoff. What is needed is a handoff model that can utilize an exact discrete-time model based on the Gaussian properties of received signal strengths.
In many papers related to handoff analysis, the MS trajectory under consideration is limited to the straight line directly connecting the two candidate base stations involved in the handoff. However, handoff behavior may depend strongly on the trajectory followed by the MS. For arbitrary MS trajectories, simulation-based methods have been the only alternative for obtaining accurate performance measures. What is also needed is a system that can utilize a representation of a general trajectory in a cellular network capable of yielding a concise characterization of handoff performance over a wide range of MS trajectories in the network.
Early work on handoff analysis has largely been based on computer simulation studies. In industrial practice, computer simulation remains the primary means for choosing key parameters to optimize the performance of modern-day wireless networks. Detailed computer simulations of wireless cellular networks require considerable computation time, making them cumbersome to use for the purposes of network design and dimensioning.
What is needed is a system capable of modeling the efficiency of handoff mechanisms in various cellular networks.